Factors impacting data integration projects
Many companies find themselves faced with serious challenges when they get started with a data integration projects, because the complexity of data integration project will typically grow with:
The number of systems in use: Data volumes tend to increase with the number of data sources you have. enterprises having nothing less than hundreds of systems, running on multiple platforms (for instance a combination of on-premise, Cloud and private hosting), in various versions and different geographical locations. When data resides in so many silos it adds a whole new complexity and security dimension to a data integration project.
The customizations made to systems: Although today many systems and applications come out-of-the-box with role-tailored functionality, most implementation projects include extra customization and development efforts to support enterprise. This can result in hundreds of custom modules or features; literally a maintenance and upgrade nightmare, but also quite a challenge to integrate the different systems.
The lack of consolidated approach to data integration: When data integration is approached as a multitude of point-to-point custom integration scripts without a common direction, then the data integration project is doomed to fail to deliver the desired business critical single view of data. Data must be synchronized in an automated and reliable manner across all platforms for a company to have one version of the truth. Errors caused by inconsistent, data and manual data entry can prove very costly for companies and disrupt business activities.
Heterogeneous application platforms: Even the applications developed over the data are heterogeneous as they are developed over a time span satisfying adhoc needs of the enterprise. This leads to heterogeneous UIs and this issue also needs to be addressed to achieve unified view at enterprise level.